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- Robert Rosenbaum, James Trousdale, Kresimir Josic
- Front. Comput. Neurosci.
- 2010

Correlations between spike trains can strongly modulate neuronal activity and affect the ability of neurons to encode information. Neurons integrate inputs from thousands of afferents. Similarly, a number of experimental techniques are designed to record pooled cell activity. We review and generalize a number of previous results that show how correlations… (More)

- Robert Rosenbaum, Kresimir Josic
- Neural Computation
- 2011

Correlations between neuronal spike trains affect network dynamics and population coding. Overlapping afferent populations and correlations between presynaptic spike trains introduce correlations between the inputs to downstream cells. To understand network activity and population coding, it is therefore important to understand how these input correlations… (More)

- Brent Doiron, Ashok Litwin-Kumar, Robert Rosenbaum, Gabriel K Ocker, Krešimir Josić
- Nature neuroscience
- 2016

Simultaneous recordings from large neural populations are becoming increasingly common. An important feature of population activity is the trial-to-trial correlated fluctuation of spike train outputs from recorded neuron pairs. Similar to the firing rate of single neurons, correlated activity can be modulated by a number of factors, from changes in arousal… (More)

Networks of model neurons with balanced recurrent excitation and inhibition produce irregular and asynchronous spiking activity. We extend the analysis of balanced networks to include the known dependence of connection probability on the spatial separation between neurons. In the continuum limit we derive that stable, balanced firing rate solutions require… (More)

- Ashok Litwin-Kumar, Robert Rosenbaum, Brent Doiron
- Journal of neurophysiology
- 2016

Recent anatomical and functional characterization of cortical inhibitory interneurons has highlighted the diverse computations supported by different subtypes of interneurons. However, most theoretical models of cortex do not feature multiple classes of interneurons and rather assume a single homogeneous population. We study the dynamics of recurrent… (More)

- Robert Rosenbaum, Andrew Zimnik, +4 authors Jonathan E Rubin
- Neurobiology of disease
- 2014

High frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a widely used treatment for Parkinson's disease, but its effects on neural activity in basal ganglia circuits are not fully understood. DBS increases the excitation of STN efferents yet decouples STN spiking patterns from the spiking patterns of STN synaptic targets. We propose… (More)

- Robert Rosenbaum, Jonathan Rubin, Brent Doiron
- PLoS Computational Biology
- 2012

Depletion of synaptic neurotransmitter vesicles induces a form of short term depression in synapses throughout the nervous system. This plasticity affects how synapses filter presynaptic spike trains. The filtering properties of short term depression are often studied using a deterministic synapse model that predicts the mean synaptic response to a… (More)

- Robert Rosenbaum, Matthew A Smith, Adam Kohn, Jonathan E Rubin, Brent Doiron
- Nature neuroscience
- 2017

Shared neural variability is ubiquitous in cortical populations. While this variability is presumed to arise from overlapping synaptic input, its precise relationship to local circuit architecture remains unclear. We combine computational models and in vivo recordings to study the relationship between the spatial structure of connectivity and correlated… (More)

- Robert Rosenbaum, James Trousdale, Krešimir Josić
- Front. Neurosci.
- 2011

Neurons integrate inputs from thousands of afferents. Similarly, some experimental techniques record the pooled activity of large populations of cells. When cells in these populations are correlated, the correlation coefficient between the collective activity of two subpopulations is typically much larger than the correlation coefficient between individual… (More)

- Kresimir Josic, Robert Rosenbaum
- SIAM Review
- 2008

The fact that the eigenvalues of the family of matrices A(t) do not determine the stability of non-autonomous differential equations x′ = A(t)x is well known. This point is often illustrated using examples in which the matrices A(t) have constant eigenvalues with negative real part, but the solutions of the corresponding differential equation grow in time.… (More)